Poverty in post -apartheid South Africa: Measurement, trends and the demography of the poor

Abstract

The dissertation comprises two major parts. The first reviews major theories of poverty and measures its extent in South Africa using four datasets (the 1996 and the 2001 censuses, the 1999 OHS and the 2004 GHS). The second part applies demographic, statistical and spatial techniques to study differentials in under-5-mortality by poverty status of households and selected socioeconomic variables using only the censuses. ^ The dissertation conceptualizes poverty as a multidimensional phenomenon that can be proxied by the socioeconomic variables that are commonly collected in African datasets. Following on Filmer and Pritchett (1998, 2001) an index of living standards is created by combining different dimensions of wellbeing, bringing together the concepts of absolute, relative and capabilities deprivation. The resulting index—the assets and capabilities poverty—demonstrates that poverty can be measured in the absence of income or expenditure data. The index is a complement, not a replacement of income measures of poverty. In addition to profiling the poor, the study shows its trend over time. Results show huge but declining inequality in living standards. Relative poverty declined from 50% in 1996 to 40% in 2004. The inequities manifest in differentials by race, urban/rural residence, province and between magisterial districts. Gauteng and Western Cape provinces are the wealthiest whilst the Eastern Cape, Limpopo and KwaZulu-Natal provinces are the poorest. This pattern is statistically significant. The district-level analysis underscores the magnitude of disparities in living conditions. Some districts have more than 95% of their households lacking even the most basic necessities of life. ^ Data quality problems in the 2001 census prevent inferences about trends in under-5-mortality. Further analysis, however, shows that the data could still be used to show differentials in childhood mortality. Despite being one of the poorest provinces, Limpopo was found to have relatively low child mortality. Poor children experience more than twice the likelihood of dying before age five as compared to non-poor children. Lastly, a spatial analysis of the data showed that child mortality is not randomly distributed. Thus, we can learn more about demographic phenomena if we incorporate spatial dimensions of the data into our analysis. ^